Most people think:
👉 If a result is statistically significant, it must be important.
But that’s not true.
In this video, we break down one of the most misunderstood concepts in data analysis:
👉 P-value vs Effect Size
You’ll learn:
✔️ What a p-value really means (in simple terms)
✔️ Why p-values can be misleading
✔️ What effect size tells you that p-values don’t
✔️ The biggest mistake analysts make
✔️ How to think like a real data analyst
✔️ Why uncertainty matters in decision-making
💡 Key Insight:
👉 A statistically significant result can still be useless.
If you work with data, business decisions, or analytics…
this video will completely change how you interpret results.
🎯 Timestamps:
00:00 – The Hidden Problem
01:10 – What is a P-Value?
02:17 – What is Effect Size?
03:12 – Why P-Values Mislead
04:06 – P-Value vs Effect Size
04:39 – Real-World Decisions
05:26 – The Classic Mistake
05:58 – Analyst Mindset
06:25 – Uncertainty Explained
07:49 – Big Picture
08:10 – Final Takeaway
📌 Subscribe to Shital’s Data Desk for:
👉 Data Analysis
👉 Power BI / Excel
👉 Real-world analytics thinking
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